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Article: Particle Deposition in Large-Scale Human Tracheobronchial Airways Predicted by Single-Path Modelling

TitleParticle Deposition in Large-Scale Human Tracheobronchial Airways Predicted by Single-Path Modelling
Authors
Keywordscomputational fluid dynamics (CFD)
deposition prediction
large-scale human airway
particle deposition mechanism
single-path modelling
Issue Date4-Mar-2023
PublisherMDPI
Citation
International Journal of Environmental Research and Public Health, 2023, v. 20, n. 5 How to Cite?
Abstract

The health effects of particles are directly related to their deposition patterns (deposition site and amount) in human airways. However, estimating the particle trajectory in a large-scale human lung airway model is still a challenge. In this work, a truncated single-path, large-scale human airway model (G3–G10) with a stochastically coupled boundary method were employed to investigate the particle trajectory and the roles of their deposition mechanisms. The deposition patterns of particles with diameters (dp) of 1–10 μm are investigated under various inlet Reynolds numbers (Re = 100–2000). Inertial impaction, gravitational sedimentation, and combined mechanism were considered. With the increasing airway generations, the deposition of smaller particles (dp < 4 μm) increased due to gravitational sedimentation, while that of larger particles decreased due to inertial impaction. The obtained formulas of Stokes number and Re can predict the deposition efficiency due to the combined mechanism in the present model, and the prediction can be used to assess the dose-effect of atmospheric aerosols on the human body. Diseases in deeper generations are mainly attributed to the deposition of smaller particles under lower inhalation rates, while diseases at the proximal generations mainly result from the deposition of larger particles under higher inhalation rates.


Persistent Identifierhttp://hdl.handle.net/10722/350620
ISSN
2019 Impact Factor: 2.849
2023 SCImago Journal Rankings: 0.808

 

DC FieldValueLanguage
dc.contributor.authorOu, Cuiyun-
dc.contributor.authorHang, Jian-
dc.contributor.authorHua, Jiajia-
dc.contributor.authorLi, Yuguo-
dc.contributor.authorDeng, Qihong-
dc.contributor.authorZhao, Bo-
dc.contributor.authorLing, Hong-
dc.date.accessioned2024-10-31T00:30:27Z-
dc.date.available2024-10-31T00:30:27Z-
dc.date.issued2023-03-04-
dc.identifier.citationInternational Journal of Environmental Research and Public Health, 2023, v. 20, n. 5-
dc.identifier.issn1661-7827-
dc.identifier.urihttp://hdl.handle.net/10722/350620-
dc.description.abstract<p>The health effects of particles are directly related to their deposition patterns (deposition site and amount) in human airways. However, estimating the particle trajectory in a large-scale human lung airway model is still a challenge. In this work, a truncated single-path, large-scale human airway model (G3–G10) with a stochastically coupled boundary method were employed to investigate the particle trajectory and the roles of their deposition mechanisms. The deposition patterns of particles with diameters (dp) of 1–10 μm are investigated under various inlet Reynolds numbers (Re = 100–2000). Inertial impaction, gravitational sedimentation, and combined mechanism were considered. With the increasing airway generations, the deposition of smaller particles (dp < 4 μm) increased due to gravitational sedimentation, while that of larger particles decreased due to inertial impaction. The obtained formulas of Stokes number and Re can predict the deposition efficiency due to the combined mechanism in the present model, and the prediction can be used to assess the dose-effect of atmospheric aerosols on the human body. Diseases in deeper generations are mainly attributed to the deposition of smaller particles under lower inhalation rates, while diseases at the proximal generations mainly result from the deposition of larger particles under higher inhalation rates.</p>-
dc.languageeng-
dc.publisherMDPI-
dc.relation.ispartofInternational Journal of Environmental Research and Public Health-
dc.subjectcomputational fluid dynamics (CFD)-
dc.subjectdeposition prediction-
dc.subjectlarge-scale human airway-
dc.subjectparticle deposition mechanism-
dc.subjectsingle-path modelling-
dc.titleParticle Deposition in Large-Scale Human Tracheobronchial Airways Predicted by Single-Path Modelling-
dc.typeArticle-
dc.identifier.doi10.3390/ijerph20054583-
dc.identifier.pmid36901592-
dc.identifier.scopuseid_2-s2.0-85149729975-
dc.identifier.volume20-
dc.identifier.issue5-
dc.identifier.eissn1660-4601-
dc.identifier.issnl1660-4601-

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